From the “worse than we thought” department comes this new climate model, but at least they acknowledge the pause.
The next few years could be “anomalously warm”, according to a new study.
Researchers have developed a mathematical model to predict how average global surface air temperatures will vary over the next few years.
The results suggest that the period from 2018 to 2022 could see an increased likelihood of extreme temperatures.
The findings are published in the journal Nature Communications.
The warming caused by emissions of greenhouse gases like CO2 is not increasing at a perfectly steady rate.
In the early years of the 21st Century, scientists pointed to a hiatus in warming. But several analyses show that the five warmest years on record all have taken place since 2010.
These variations from year-to-year do not affect the long-term trend in warming temperatures.
Now, a new method for trying to predict global temperatures suggests the next few years will be hotter than expected.
Rather than using traditional climate simulation techniques, Florian Sévellec, from the CNRS in Brest, France, and Sybren S Drijfhout, from the University of Southampton, developed a statistical method to search through simulations of climatic conditions in the 20th and 21st Century and look for situations that are comparable to the present day.
Future possibilities
The team then used these climatic “analogues” to deduce future possibilities.
In particular, the anomalous warmth predicted over the next few years is due to a low probability of intense cold climatic events.
Once the algorithm is “learned” (a process which takes a few minutes), predictions are obtained in a few hundredths of a second on a laptop. In comparison, supercomputers require a week using traditional simulation methods.
Gabi Hegerl, professor of climate system science at the University of Edinburgh, who was not involved with the study, said: “The authors have tried to predict whether global climate variability will make the next years warmer or cooler overall than the mean warming trend. They have skilfully used worldwide climate model data for previous years to calculate probabilities for the next few years.
“The findings suggest it’s more likely we’ll get warmer years than expected in the next few years.
Full article here
As noted further in the article, the result is “purely statistical”, so take it with a grain of salt, because I suspect the “learning” part of the algorithm doesn’t handle long-term natural variation well at all, just like the short term memory of humans often can’t recall the intensity of weather events in the far past. Of course, humans programmed this, so…
UPDATE: Here’s the paper:
https://www.nature.com/articles/s41467-018-05442-8
A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend
Abstract
In a changing climate, there is an ever-increasing societal demand for accurate and reliable interannual predictions. Accurate and reliable interannual predictions of global temperatures are key for determining the regional climate change impacts that scale with global temperature, such as precipitation extremes, severe droughts, or intense hurricane activity, for instance. However, the chaotic nature of the climate system limits prediction accuracy on such timescales. Here we develop a novel method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. The prediction accuracy is equivalent to operational forecasts and its reliability is high. The post-1998 global warming hiatus is well predicted. For 2018–2022, the probabilistic forecast indicates a warmer than normal period, with respect to the forced trend. This will temporarily reinforce the long-term global warming trend. The coming warm period is associated with an increased likelihood of intense to extreme temperatures. The important numerical efficiency of the method (a few hundredths of a second on a laptop) opens the possibility for real-time probabilistic predictions carried out on personal mobile devices.
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Hmmm, more wild ass guesses. My wild ass guess is that in a few years they’ll either: 1) drop all reference to this ‘new’ model, or 2) they’ll say they just need to make a few “tweaks” to the model, or the data record.
tweaking the data record will be in the interest of science. It has to match the models.
“… method to search through simulations of climatic conditions…”
I might give the study more credibility if they’d searched for past observation of conditions like present, and then made predictions based on what followed in fact.
https://www.theguardian.com/environment/climate-consensus-97-per-cent/2013/dec/23/global-warming-intensify-droughts
http://scienceblogs.com/gregladen/2015/02/23/global-warming-changing-weather-in-the-us-northeast/
Oh. Hum.
Winter in the UK is going to be cold.
“people just wont know what a good prediction is…”
Keep plenty of screenshots and other copies of this bit of magical thinking.
The chances of this being accurate are close yo nil.
When the prediction fails, and the authors pretend they never made the prediction, confront them.
Notice that like basically all climate predictions, they waited until something happens – a heatwave- and then predict more of it.
Just like those predictions of more hurricanes after the 2005 season.
And how did that turn out?
Huh…OK, I am not sure where I am on this report.
I am perfectly willing to believe that one could predict (in general with a higher than random probability) hot and cool summers up to a few years out. Unfortunately without an actual stated temperature of the areas you are predicting, you will tend to claim victory if ANY place is hotter…so not useful.
Using climate model predictions that were tuned to manipulated historic data for your “analogs” means you have tied your new model into historic data in a very non-obvious, complex way that will defy understanding…so not useful.
You are still tying your new model into the belief that CO2 controls everything instead of letting it tell you what mattered…so not useful.
You have not differentiated your prediction from that of the Null Hypothesis (where CO2 is NOT the controlling factor) because most everyone agrees there is natural warming occurring. If natural warming produces a warm summer, you declare victory – even though your hypothesis is still not tested. So…yup…not useful.
Its a good idea…train a computer model to recognize patterns from historical data and predict the next one or two years out, but the implementation is…well…not useful. 😉
Am expecting the snow cover to set in early this year over NE Canada and NW Russia.
Increased jet stream activity in the Arctic is going to lead to the risk of early season cold in these areas.
June was strangely hot in Oklahoma but August has been 15-20 degrees cooler than usual. Very strange. Could this portend a very cold winter? Or just an early mild winter?
“Once the algorithm is “learned” (a process which takes a few minutes), predictions are obtained in a few hundredths of a second on a laptop. In comparison, supercomputers require a week using traditional simulation methods.”
This passes for science these days? We are doomed! Well, at least we are at the start of the predicted period, 2018. 2022 is not far away. No wait, was the laptop running Windows 7 by any chance? If so, 2022 is the end of the world for Windows 7 users.
We’re DOOOOOOOOOMED!
‘The next few years could be “anomalously warm”, according to a new study …’.
Creating expectations in the general population is a propaganda technique in this case the BBC audience, the purpose of the report is simply to reinforce an accepted narrative whatever the outcome:
“The propagandist seeks to change the way people understand an issue or situation for the purpose of changing their actions and expectations in ways that are desirable to the interest group …” (Wiki).
CLIMATE SCIENCE MUST BE DESTROYED BEFORE IT DESTROYS ALL OF SCIENCE. In the future I will be like CATO denouncing the Carthaginians. The difference is that the Carthaginians were no more evil than the Romans. However Climate science was born of evil whereas science itself is the search for the truth. Meteorology is the study of the weather. We wlll always need it. However since we can’t ever know the future of climate as even admitted by the IPCC, we have no need of trying to forecast it. 40 years of trying has evolved into the evil of alarmism that you see today.
**************************************************************************************************
CLIMATE SCIENCE MUST BE DESTROYED
“Researchers have developed a mathematical model to predict…” is code for “Caution–Unmitigated Nonsense Ahead!”
“Researchers have developed a mathematical model to predict…” is code for “Caution–Nonsense Ahead!”
“…This will temporarily reinforce the long-term global warming trend…”
Why does it need reinforcement, and why would this reinforcement only by temporary?
“We put that data in dozens of different climate models and ignore the ones that look wrong to us.”
(Dilbert- Scott Adams).
Excellent. So now they won’t need all those expensive computers anymore.
From the article: “the anomalous warmth predicted over the next few years is due to a low probability of intense cold climatic events”
And from the abstract: The coming warm period is associated with an increased likelihood of intense to extreme temperatures”
Something wrong there
“The post-1998 global warming hiatus is well predicted.”
Predicted? I don’t think they know what that word means.
I will not even bother to read about yet another model. Look up.
Mainstream media lick their lips at a story like this. In NZ it has been in both major news paper networks and the Government financed National Radio. Its exactly what I like to see. Give them plenty of rope and they will hang themselves – sooner or later. In this case it could be sooner.
Regards
M
The climate will get so bad in Nuh Zilund that the PM may consider moving The Beehive, and Govn’t, to Melbourne!
It seems that summer ends in the UK.
Heads hotter Tails cooler?
In particular, the anomalous warmth predicted over the next few years is due to a low probability of intense cold climatic events.
The physical reason for the general lack of intense cold events during the solar minimum years and early rising phase of the following cycle is TSI is either very flat or is increasing then without large enough sunspots for TSI to drop again below solar minimum levels.
Each solar cycle since 1960 has had about a total 0.6C swing in monthly HadSST3 data. SC24 is shown below in yearly data. HadSST3 rose about 0.3C between the solar min and four years later. If SST3 ends at this solar minimum around 0.3-0.4C, and then the next cycle were to also add another 0.3C over the next four years, 2022 temps would exceed the 2016 yearly record. The top of SC25 will definitely see record monthly temperatures again unless the next solar max sunspot number is very very low.
During their 4 year forecast window we will see another solar cycle onset El Nino, as we did in 2009/10, and then the climb to the solar max after the La Nina. In the fourth year after the last solar minimum, 2012, TSI was above the ocean warming threshold, making it a hot year, esp the second half.
2018-2022 summer land temperatures will continue to be high from drier skies high UV index conditions brought about by solar minimum low TSI low tropical evaporation.
That the authors used a probabilistic statistical method without understanding the solar influence is purely curve-fitting that can be done with enough data and a neural net. They can be right without knowing why.
Every bit of this is determined by solar cycles, which is why I have warned skeptics this year against overblown solar cooling predictions, and about being ready for SC25 warming.
“They have skilfully used worldwide climate model data for previous years to calculate probabilities for the next few years.”
Computer models? Skillful? Yeah right!